A high percentage of prematurely born children suffer from neurodevelopmental and learning disabilities later in life. To date, few reliable causative or predictive factors have been identified that can be recognized during the early postnatal period and relate to poor outcome in these individuals. White matter injury is commonly identified on magnetic resonance imaging (MRI) studies of prematurely born infants, but the consequences of these lesions on brain morphology and neurodevelopmental outcome has not been reliably determined. Abnormal white matter and related gray matter integrity visible on MRI may result in geometrically quantifiable disturbances from normal brain development, which are detectable in neonatal MRI. We hypothesize that such damage, relating to specific functional abilities and occurring early in development, may be highly focal and anatomically subtle in nature. This project will develop state of the art image analysis techniques specifically to study the developing premature neonatal brain from high resolution MRI data. This is initially aimed at detecting relationships between early brain development and clinical outcome at 30 months, in order to identify consistent anatomical features that predict outcome. Specifically, it will develop techniques to study the two main quantifiable aspects of developmental neuroanatomy: patterns of local and global tissue volume and the resulting patterns of cortical folding. It will combine deformation based morphometric techniques, specialized tissue segmentation algorithms, together with methods of brain surface curvature analysis. New statistical analysis methods will be developed that allow spatial hypothesis free analysis of patterns of tissue growth and surface curvature, in order to detect early focal disturbances in development that predict poor outcome. Finally, we will evaluate these techniques by looking for specific anatomical patterns related to visual and motor outcome abnormalities. Such techniques have a range of applications in the many new in-vivo studies of premature brain anatomy now being performed. They promise to reveal patterns of injury that are potentially avoidable and may allow interventions at early ages when brain plasticity is high. Ultimately, these improvements in our understanding may help to improve developmental outcome.

Public Health Relevance

Premature birth is one of the major causes of childhood neuropsychiatric disorder. This project will develop and apply new methods of detecting brain abnormalities from MRI scans of the premature neonate. The will specifically allow the spatial mapping of patterns of normal and abnormal brain tissue growth after premature birth. These methods will contribute to our understanding of brain development in premature babies and reveal possible new neuronanatomical markers for poor neurological outcome that allow early clinical intervention.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS061957-06
Application #
8514085
Study Section
Developmental Brain Disorders Study Section (DBD)
Program Officer
Hirtz, Deborah G
Project Start
2009-08-01
Project End
2014-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
6
Fiscal Year
2013
Total Cost
$322,440
Indirect Cost
$113,741
Name
University of Washington
Department
Pediatrics
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
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Liu, Mengyuan; Kitsch, Averi; Miller, Steven et al. (2016) Patch-based augmentation of Expectation-Maximization for brain MRI tissue segmentation at arbitrary age after premature birth. Neuroimage 127:387-408
Zwicker, Jill G; Miller, Steven P; Grunau, Ruth E et al. (2016) Smaller Cerebellar Growth and Poorer Neurodevelopmental Outcomes in Very Preterm Infants Exposed to Neonatal Morphine. J Pediatr 172:81-87.e2
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Cheng, Xi; Wilm, Jakob; Seshamani, Sharmishtaa et al. (2013) Adapting parcellation schemes to study fetal brain connectivity in serial imaging studies. Conf Proc IEEE Eng Med Biol Soc 2013:73-6

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